Ding-Xuan Zhou

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82 件の論文

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共著者

Shao-Bo LinXi'an Jiaotong University確認したメールアドレス: xjtu.edu.cn
Yiming YingSchool of Mathematics and Statistics, University of Sydney確認したメールアドレス: sydney.edu.au
Wu, QiangThe University of Tennessee, Knoxville確認したメールアドレス: utk.edu
Stephen SMALEprofessor cityu of hong kong確認したメールアドレス: cityu.edu.hk
Yunwen LeiThe University of Hong Kong確認したメールアドレス: hku.hk
Jun FanHong Kong Baptist University確認したメールアドレス: hkbu.edu.hk
Xin Guo 郭昕School of Mathematics and Physics, The University of Queensland確認したメールアドレス: uq.edu.au
Junhong LinZhejiang University確認したメールアドレス: zju.edu.cn
Andreas ChristmannUniversity of Bayreuth, Department of Mathematics確認したメールアドレス: uni-bayreuth.de
Quan-Wu XiaoMicrosoft確認したメールアドレス: mail.ustc.edu.cn
Gui-Bo YeDepartment of Mathematics, Hong Kong University of Science and Technology確認したメールアドレス: ust.hk
Lorenzo RosascoMaLGa Machine Learning Genoa Center - Università degli Studi di Genova確認したメールアドレス: unige.it
Massimiliano PontilIstituto Italiano di Tecnologia & University College London確認したメールアドレス: iit.it
Ming YuanColumbia University確認したメールアドレス: columbia.edu
Marius KloftProfessor, RPTU Kaiserslautern-Landau確認したメールアドレス: cs.uni-kl.de
Yunlong FengState University of New York at Albany確認したメールアドレス: albany.edu
Xiangyu ChangSchool of Management, Xi'an Jiaotong University確認したメールアドレス: xjtu.edu.cn
Hrushikesh MhaskarDistinguished Research Professor, Claremont Graduate University確認したメールアドレス: cgu.edu
Wotao YinDAMO Academy, Alibaba Group US確認したメールアドレス: alibaba-inc.com
Jianzhong WangProfessor of Mathematics, Sam Houston State University確認したメールアドレス: shsu.edu

フォロー

Ding-Xuan Zhou

University of Sydney

確認したメールアドレス: sydney.edu.au - ホームページ

theory of deep learning statistical learning wavelets approximation theory


タイトル引用回数順公開年順タイトル順	引用先引用先	年
Learning theory: an approximation theory viewpoint F Cucker, DX Zhou Cambridge University Press, 2007	1026	2007
Learning theory estimates via integral operators and their approximations S Smale, DX Zhou Constructive approximation 26 (2), 153-172, 2007	743	2007
Universality of deep convolutional neural networks DX Zhou Applied and computational harmonic analysis 48 (2), 787-794, 2020	739	2020
The covering number in learning theory DX Zhou Journal of Complexity 18 (3), 739-767, 2002	420	2002
Support vector machine soft margin classifiers: error analysis DR Chen, Q Wu, Y Ying, DX Zhou Journal of Machine Learning Research 5 (Sep), 1143-1175, 2004	320	2004
Estimating the approximation error in learning theory S Smale, DX Zhou Analysis and Applications 1 (01), 17-41, 2003	319	2003
Shannon sampling and function reconstruction from point values S Smale, DX Zhou Bulletin of the American Mathematical Society 41 (3), 279-305, 2004	304	2004
Capacity of reproducing kernel spaces in learning theory DX Zhou IEEE Transactions on information theory 49 (7), 1743-1752, 2003	295	2003
Learning rates of least-square regularized regression Q Wu, Y Ying, DX Zhou Foundations of computational mathematics 6, 171-192, 2006	287	2006
Theory of deep convolutional neural networks: Downsampling DX Zhou Neural Networks 124, 319-327, 2020	268	2020
Shannon sampling II: Connections to learning theory S Smale, DX Zhou Applied and Computational Harmonic Analysis 19 (3), 285-302, 2005	260	2005
Towards understanding the spectral bias of deep learning Y Cao, Z Fang, Y Wu, DX Zhou, Q Gu arXiv preprint arXiv:1912.01198, 2019	252	2019
Distributed learning with regularized least squares SB Lin, X Guo, DX Zhou Journal of Machine Learning Research 18 (92), 1-31, 2017	233	2017
SVM soft margin classifiers: linear programming versus quadratic programming Q Wu, DX Zhou Neural computation 17 (5), 1160-1187, 2005	232	2005
Multi-kernel regularized classifiers Q Wu, Y Ying, DX Zhou Journal of Complexity 23 (1), 108-134, 2007	217	2007
Derivative reproducing properties for kernel methods in learning theory DX Zhou Journal of computational and Applied Mathematics 220 (1-2), 456-463, 2008	200	2008
Online learning with Markov sampling S Smale, DX Zhou Analysis and Applications 7 (01), 87-113, 2009	177	2009
Deep distributed convolutional neural networks: Universality DX Zhou Analysis and applications 16 (06), 895-919, 2018	167	2018
Approximation with polynomial kernels and SVM classifiers DX Zhou, K Jetter Advances in Computational Mathematics 25 (1), 323-344, 2006	155	2006
Analysis of support vector machine classification. Q Wu, DX Zhou Journal of Computational Analysis & Applications 8 (2), 2006	155	2006

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